Human Density Detection and Dynamic Small Cell Activation System Using Thermal Camera and Lidar Fusion

Abstract

The invention is an intelligent system and method that uses thermal camera and LIDAR sensor fusion technology to detect human density in real time and dynamically activate / deactivate small cell base stations based on this detection, with the aim of optimizing capacity and improving energy efficiency in mobile telecommunication networks. The system combines heat signature data from thermal camera sensors with three-dimensional distance and geometry data from LIDAR (Light Detection and Ranging) sensors (sensor fusion) to detect, count, and map the presence of humans with high accuracy. This data is analyzed using machine learning algorithms to generate future density predictions, and accordingly, the system automatically determines when small cell base stations (pico cell, femto cell, remote radio head - RRH) should be active or passive.This allows network capacity to dynamically adapt to user demand, preventing unnecessary energy consumption and optimizing QoS (Quality of Service) parameters.